People
Principal Investigator
Ph.D. track
SL M.S.+Ph.D. Sangyoon Lee
Exploiting Discrete Vision Tokenization for MLLMs
Unifying modality-specific features to enable more efficient and deeper multimodal intelligence.
MP M.S.+Ph.D. Minjae Park
ML Efficiency: data & inference
Making AI cheaper to run — so more people and teams can actually afford to use it
HO M.S.+Ph.D. Hyunjong Ok
Advancing Audio Technologies for Multimodal Intelligence 🔈
Diagnostic Evaluation of Multimodal AI
JB Ph.D. Jiyun Bae
Robustness of Reasoning Vision-Language Models 🕶️
Aspiring to build AI systems that perceive the visual world as faithfully as they reason about it.
TY M.S.+Ph.D. Taesun Yeom
Improving generalization through implicit bias
Bridging theory and practice in deep learning
YK M.S.+Ph.D. Yongjun Kim
Improving reasoning models with test-time intervention
Interested in improving intelligence in test-time (e.g., test-time scaling, test-time training)
HK M.S.+Ph.D. Hyeonjun Kim
Image Compression For Vision-Language-Action Models 🤖
A highly self-motivated researcher investigating how to integrate different modalities.
M.S. track
JR M.S. Jegwang Ryu
Uncertainty Quantification in Large-Scale Models
Developing efficient and reliable AI sysyem for real-world applications
SK M.S. Seunghyun Kim
Enable high-FPS video processing with low overhead 🎥
Discovering overlooked problems from new perspectives
ML M.S. Minhee Lee
Understanding Prompt Ignoring in mmDiT 🎨
Aiming to enhance performance by tackling fundamental causes.


